Evolution of complexity in RNA-like replicator systems

The Evolutionary Transition of the RNA World to Obcells to Cellular-Based Life

The obcell hypothesis is a proposed route for the RNA world to develop into a primitive cellular one. It posits that this transition began with the emergence of the proto-ribosome which enabled RNA to colonise the external surface of lipids by the synthesis of amphipathic peptidyl-RNAs. The obcell hypothesis also posits that the emergence of a predation-based ecosystem provided a selection mechanism for continued sophistication amongst early life forms. Here, I argue for this hypothesis owing to its significant explanatory power; it offers a rationale why a ribosome which initially was capable only of producing short non-coded peptides was advantageous and it forgoes issues related to maintaining a replicating RNA inside a lipid enclosure. I develop this model by proposing that the evolutionary selection for improved membrane anchors resulted in the emergence of primitive membrane pores which enabled obcells to gradually evolve into a cellular morphology. Moreover, I introduce a model of obcell production which advances that tRNAs developed from primers of the RNA world.

Plausible pathway for a host-parasite molecular replication network to increase its complexity through Darwinian evolution

How the complexity of primitive self-replication molecules develops through Darwinian evolution remains a mystery with regards to the origin of life. Theoretical studies have proposed that coevolution with parasitic replicators increases network complexity by inducing inter-dependent replication. Particularly, Takeuchi and Hogeweg proposed a complexification process of replicator networks by successive appearance of a parasitic replicator followed by the addition of a new host replicator that is resistant to the parasitic replicator. However, the feasibility of such complexification with biologically relevant molecules is still unknown owing to the lack of an experimental model. Here, we investigated the plausible complexification pathway of host-parasite replicators using both an experimental host-parasite RNA replication system and a theoretical model based on the experimental system. We first analyzed the parameter space that allows for sustainable replication in various replication networks ranging from a single molecule to three-member networks using computer simulation. The analysis shows that the most plausible complexification pathway from a single host replicator is the addition of a parasitic replicator, followed by the addition of a new host replicator that is resistant to the parasite, consistent with the previous study by Takeuchi and Hogeweg. We also provide evidence that the pathway actually occurred in our previous evolutionary experiment. These results provide experimental evidence that a population of a single replicator spontaneously evolves into multi-replicator networks through coevolution with parasitic replicators.

RNA World Modeling: A Comparison of Two Complementary Approaches

Simple Summary

Despite years of dedicated research, scientists are still not sure what the first ”living” cell would have looked like. One of the most well-known hypotheses is the RNA world hypothesis, which assumes that, in the beginning, life relied on RNA molecules instead of DNA as information carriers and primitive enzymes. The population of such RNAs is made up of self-replicating molecules (replicases) that could make copies of themselves and parasite molecules that could only be copied by replicases. In this study, we further investigated the interplay between these hypothetical prebiotic RNA species, since it plays a crucial role in generating diversity and complexity in prebiotic molecular evolution. We compared two approaches that are commonly used to investigate such simple prebiotic systems, representing different modeling and observation scales—namely, microscopic and macroscopic. In both cases, we were able to obtain consistent results.

Abstract

The origin of life remains one of the major scientific questions in modern biology. Among many hypotheses aiming to explain how life on Earth started, RNA world is probably the most extensively studied. It assumes that, in the very beginning, RNA molecules served as both enzymes and as genetic information carriers. However, even if this is true, there are many questions that still need to be answered—for example, whether the population of such molecules could achieve stability and retain genetic information for many generations, which is necessary in order for evolution to start. In this paper, we try to answer this question based on the parasite–replicase model (RP model), which divides RNA molecules into enzymes (RNA replicases) capable of catalyzing replication and parasites that do not possess replicase activity but can be replicated by RNA replicases. We describe the aforementioned system using partial differential equations and, based on the analysis of the simulation, surmise general rules governing its evolution. We also compare this approach with one where the RP system is modeled and implemented using a multi-agent modeling technique. We show that approaching the description and analysis of the RP system from different perspectives (microscopic represented by MAS and macroscopic depicted by PDE) provides consistent results. Therefore, applying MAS does not lead to erroneous results and allows us to study more complex situations where many cases are concerned, which would not be possible through the PDE model.

Nothing in evolution makes sense except in the light of parasitism: evolution of complex replication strategies

Parasitism emerges readily in models and laboratory experiments of RNA world and would lead to extinction unless prevented by compartmentalization or spatial patterning. Modelling replication as an active computational process opens up many degrees of freedom that are exploited to meet environmental challenges, and to modify the evolutionary process itself. Here, we use automata chemistry models and spatial RNA-world models to study the emergence of parasitism and the complexity that evolves in response. The system is initialized with a hand-designed replicator that copies other replicators with a small chance of point mutation. Almost immediately, short parasites arise; these are copied more quickly, and so have an evolutionary advantage. The replicators also become shorter, and so are replicated faster; they evolve a mechanism to slow down replication, which reduces the difference of replication rate of replicators and parasites. They also evolve explicit mechanisms to discriminate copies of self from parasites; these mechanisms become increasingly complex. New parasite species continually arise from mutated replicators, rather than from evolving parasite lineages. Evolution itself evolves, e.g. by effectively increasing point mutation rates, and by generating novel emergent mutational operators. Thus, parasitism drives the evolution of complex replicators and complex ecosystems.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

Multi-agent approach to sequence structure simulation in the RNA World hypothesis

The origins of life on Earth have been the subject of inquiry since the early days of philosophical thought and are still intensively investigated by the researchers around the world. One of the theories explaining the life emergence, that gained the most attention recently is the RNA World hypothesis, which assumes that life on Earth was sparked by replicating RNA chains. Since wet lab analysis is time-consuming, many mathematical and computational approaches have been proposed that try to explain the origins of life. Recently proposed one, based on the work by Takeuchi and Hogeweg, addresses the problem of interplay between RNA replicases and RNA parasitic species, which is crucial for understanding the first steps of prebiotic evolution. In this paper, the aforementioned model has been extended and modified by introducing RNA sequence (structure) information and mutation rate close to real one. It allowed to observe the simple evolution mechanisms, which could have led to the more complicated systems and eventually, to the formation of the first cells. The main goal of this study was to determine the conditions that allowed the spontaneous emergence and evolution of the prebiotic replicases equipped with simple functional domains within a large population. Here we show that polymerase ribozymes could have appeared randomly and then quickly started to copy themselves in order for the system to reach equilibrium. It has been shown that evolutionary selection works even in the simplest systems.

Emergence and diversification of a host-parasite RNA ecosystem through Darwinian evolution

In prebiotic evolution, molecular self-replicators are considered to develop into diverse, complex living organisms. The appearance of parasitic replicators is believed inevitable in this process. However, the role of parasitic replicators in prebiotic evolution remains elusive. Here, we demonstrated experimental coevolution of RNA self-replicators (host RNAs) and emerging parasitic replicators (parasitic RNAs) using an RNA-protein replication system we developed. During a long-term replication experiment, a clonal population of the host RNA turned into an evolving host-parasite ecosystem through the continuous emergence of new types of host and parasitic RNAs produced by replication errors. The host and parasitic RNAs diversified into at least two and three different lineages, respectively, and they exhibited evolutionary arms-race dynamics. The parasitic RNA accumulated unique mutations, thus adding a new genetic variation to the whole replicator ensemble. These results provide the first experimental evidence that the coevolutionary interplay between host-parasite molecules plays a key role in generating diversity and complexity in prebiotic molecular evolution.

Viral Symbiosis in the Origins and Evolution of Life with a Particular Focus on the Placental Mammals

Advances in understanding over the last decade or so highlight the need for a reappraisal of the role of viruses in relation to the origins and evolution of cellular life, as well as in the homeostasis of the biosphere on which all of life depends. The relevant advances have, in particular, revealed an important contribution of viruses to the evolution of the placental mammals, while also contributing key roles to mammalian embryogenesis, genomic evolution, and physiology. Part of this reappraisal will include the origins of viruses, a redefinition of their quintessential nature, and a suggestion as to how we might view viruses in relation to the tree of life.

The origin of the central dogma through conflicting multilevel selection

The central dogma of molecular biology rests on two kinds of asymmetry between genomes and enzymes: informatic asymmetry, where information flows from genomes to enzymes but not from enzymes to genomes; and catalytic asymmetry, where enzymes provide chemical catalysis but genomes do not. How did these asymmetries originate? Here, we show that these asymmetries can spontaneously arise from conflict between selection at the molecular level and selection at the cellular level. We developed a model consisting of a population of protocells, each containing a population of replicating catalytic molecules. The molecules are assumed to face a trade-off between serving as catalysts and serving as templates. This trade-off causes conflicting multilevel selection: serving as catalysts is favoured by selection between protocells, whereas serving as templates is favoured by selection between molecules within protocells. This conflict induces informatic and catalytic symmetry breaking, whereby the molecules differentiate into genomes and enzymes, establishing the central dogma. We show mathematically that the symmetry breaking is caused by a positive feedback between Fisher’s reproductive values and the relative impact of selection at different levels. This feedback induces a division of labour between genomes and enzymes, provided variation at the molecular level is sufficiently large relative to variation at the cellular level, a condition that is expected to hinder the evolution of altruism. Taken together, our results suggest that the central dogma is a logical consequence of conflicting multilevel selection.

Detecting life signatures with RNA sequence similarity measures

The RNA World is currently the most plausible hypothesis for explaining the origins of life on Earth. The supporting body of evidence is growing and it comes from multiple areas, including astrobiology, chemistry, biology, mathematics, and, in particular, from computer simulations. Such methods frequently assume the existence of a hypothetical species on Earth, around three billion years ago, with a base sequence probably dissimilar from any in known genomes. However, it is often hard to verify whether or not a hypothetical sequence has the characteristics of biological sequences, and is thus likely to be functional. The primary objective of the presented research was to verify the possibility of building a computational 'life probe' for determining whether a given genetic sequence is biological, and assessing the sensitivity of such probes to the signatures of life present in known biological sequences. We have proposed decision algorithms based on the normalized compression distance (NCD) and Levenshtein distance (LD). We have validated the proposed method in the context of the RNA World hypothesis using short genetic sequences shorter than the error threshold value (i.e., 100 nucleotides). We have demonstrated that both measures can be successfully used to construct life probes that are significantly better than a random decision procedure, while varying from each other when it comes to detailed characteristics. We also observed that fragments of sequences related to replication have better discriminatory power than sequences having other molecular functions. In a broader context, this shows that the signatures of life in short RNA samples can be effectively detected using relatively simple means.

Models of Replicator Proliferation Involving Differential Replicator Subunit Stability

Several models for the origin of life involve molecules that are capable of self-replication, such as self-replicating polymers composed of RNA or DNA or amino acids. Here we consider a hypothetical replicator (AB) composed of two subunits, A and B. Programs written in Python and C programming languages were used to model AB replicator abundance as a function of cycles of replication (iterations), under specified hypothetical conditions. Two non-exclusive models describe how a reduced stability for B relative to A can have an advantage for replicator activity and/or evolution by generating free A subunits. In model 1, free A subunits associate with AB replicators to create AAB replicators with greater activity. In simulations, reduced stability of B was beneficial when the replication activity of AAB was greater than two times the replication activity of AB. In model 2, the free A subunit is inactive for some number of iterations before it re-creates the B subunit. A re-creates the B subunit with an equal chance of creating B or B', where B' is a mutant that increases AB' replicator activity relative to AB. In simulations, at moderate number of iterations (< 15), a shorter survival time for B is beneficial when the stability of B is greater than the inactive time of A. The results are consistent with the hypothesis that reduced stability for a replicator subunit can be advantageous under appropriate conditions.

Physical foundations of biological complexity

Biological systems reach hierarchical complexity that has no counterpart outside the realm of biology. Undoubtedly, biological entities obey the fundamental physical laws. Can today's physics provide an explanatory framework for understanding the evolution of biological complexity? We argue that the physical foundation for understanding the origin and evolution of complexity can be gleaned at the interface between the theory of frustrated states resulting in pattern formation in glass-like media and the theory of self-organized criticality (SOC). On the one hand, SOC has been shown to emerge in spin-glass systems of high dimensionality. On the other hand, SOC is often viewed as the most appropriate physical description of evolutionary transitions in biology. We unify these two faces of SOC by showing that emergence of complex features in biological evolution typically, if not always, is triggered by frustration that is caused by competing interactions at different organizational levels. Such competing interactions lead to SOC, which represents the optimal conditions for the emergence of complexity. Competing interactions and frustrated states permeate biology at all organizational levels and are tightly linked to the ubiquitous competition for limiting resources. This perspective extends from the comparatively simple phenomena occurring in glasses to large-scale events of biological evolution, such as major evolutionary transitions. Frustration caused by competing interactions in multidimensional systems could be the general driving force behind the emergence of complexity, within and beyond the domain of biology.

Conceptualizing the origin of life in terms of evolution

In this opinion piece, we discuss how to place evolution in the context of origin-of-life research. Our discussion starts with a popular definition: 'life is a self-sustained chemical system capable of undergoing Darwinian evolution'. According to this definition, the origin of life is the same as the origin of evolution: evolution is the 'end' of the origin of life. This perspective, however, has a limitation, in that the ability of evolution in and of itself is insufficient to explain the origin of life as we know it, as indicated by Spiegelman's and Lincoln and Joyce's experiments. This limitation provokes a crucial question: What conditions are required for replicating systems to evolve into life? From this perspective, the origin of life includes the emergence of life through evolution: evolution is a 'means' of the origin of life. After reviewing Eigen's pioneering work on this question, we mention our ongoing work suggesting that a key condition might be conflicting multi-level evolution. Taken together, there are thus two questions regarding the origin of life: how evolution gets started, and how evolution produces life. Evolution is, therefore, at the centre of the origin of life, where the two lines of enquiry must meet.This article is part of the themed issue 'Reconceptualizing the origins of life'.

Inevitability of the emergence and persistence of genetic parasites caused by evolutionary instability of parasite-free states

Genetic parasites, including viruses and mobile genetic elements, are ubiquitous among cellular life forms, and moreover, are the most abundant biological entities on earth that harbor the bulk of the genetic diversity. Here we examine simple thought experiments to demonstrate that both the emergence of parasites in simple replicator systems and their persistence in evolving life forms are inevitable because the putative parasite-free states are evolutionarily unstable.

REVIEWERS

This article has been reviewed by Yitzhak Pilpel, Bojan Zagrovic, and Eric van Nimwegen.

Evolutionary Conflict Leads to Innovation: Symmetry Breaking in a Spatial Model of RNA-Like Replicators

Molecules that replicate in trans are vulnerable to evolutionary extinction because they decrease the catalysis of replication to become more available as a template for replication. This problem can be alleviated with higher-level selection that clusters molecules of the same phenotype, favouring those groups that contain more catalysis. Here, we study a simple replicator model with implicit higher-level selection through space. We ask whether the functionality of such system can be enhanced when molecules reproduce through complementary replication, representing RNA-like replicators. For high diffusion, symmetry breaking between complementary strands occurs: one strand becomes a specialised catalyst and the other a specialised template. In ensemble, such replicators can modulate their catalytic activity depending on their environment, thereby mitigating the conflict between levels of selection. In addition, these replicators are more evolvable, facilitating survival in extreme conditions (i.e., for higher diffusion rates). Our model highlights that evolution with implicit higher-level selection—i.e., as a result of local interactions and spatial patterning—is very flexible. For different diffusion rates, different solutions to the selective conflict arise. Our results support an RNA World by showing that complementary replicators may have various ways to evolve more complexity.

Topological and thermodynamic factors that influence the evolution of small networks of catalytic RNA species

An RNA-directed recombination reaction can result in a network of interacting RNA species. It is now becoming increasingly apparent that such networks could have been an important feature of the RNA world during the nascent evolution of life on the Earth. However, the means by which such small RNA networks assimilate other available genotypes in the environment to grow and evolve into the more complex networks that are thought to have existed in the prebiotic milieu are not known. Here, we used the ability of fragments of the Azoarcus group I intron ribozyme to covalently self-assemble via genotype-selfish and genotype-cooperative interactions into full-length ribozymes to investigate the dynamics of small (three- and four-membered) networks. We focused on the influence of a three-membered core network on the incorporation of additional nodes, and on the degree and direction of connectivity as single new nodes are added to this core. We confirmed experimentally the predictions that additional links to a core should enhance overall network growth rates, but that the directionality of the link (a "giver" or a "receiver") impacts the growth of the core itself. Additionally, we used a simple mathematical model based on the first-order effects of lower-level interactions to predict the growth of more complex networks, and find that such a model can, to a first approximation, predict the ordinal rankings of nodes once a steady-state distribution has been reached.

Tag mechanism as a strategy for the RNA replicase to resist parasites in the RNA world

The idea that life may have started with an “RNA world” is attractive. Wherein, a crucial event (perhaps at the very beginning of the scenario) should have been the emergence of a ribozyme that catalyzes its own replication, i.e., an RNA replicase. Although now there is experimental evidence supporting the chemical feasibility of such a ribozyme, the evolutionary dynamics of how the replicase could overcome the “parasite” problem (because other RNAs may also exploit this ribozyme) and thrive, as described in the scenario, remains unclear. It has been suggested that spatial limitation may have been important for the replicase to confront parasites. However, more studies showed that such a mechanism is not sufficient when this ribozyme’s altruistic trait is taken into full consideration. “Tag mechanism”, which means labeling the replicase with a short subsequence for recognition in replication, may be a further mechanism supporting the thriving of the replicase. However, because parasites may also “equip” themselves with the tag, it is far from clear whether the tag mechanism could take effect. Here, we conducted a computer simulation using a Monte-Carlo model to study the evolutionary dynamics surrounding the development of a tag-driven (polymerase-type) RNA replicase in the RNA world. We concluded that (1) with the tag mechanism the replicase could resist the parasites and become prosperous, (2) the main underlying reason should be that the parasitic molecules, especially those strong parasites, are more difficult to appear in the tag-driven system, and (3) the tag mechanism has a synergic effect with the spatial limitation mechanism–while the former provides “time” for the replicase to escape from parasites, the latter provides “space” for the replicase to escape. Notably, tags may readily serve as “control handles”, and once the tag mechanism was exploited, the evolution towards complex life may have been much easier.

Co-operation between Polymerases and Nucleotide Synthetases in the RNA World

It is believed that life passed through an RNA World stage in which replication was sustained by catalytic RNAs (ribozymes). The two most obvious types of ribozymes are a polymerase, which uses a neighbouring strand as a template to make a complementary sequence to the template, and a nucleotide synthetase, which synthesizes monomers for use by the polymerase. When a chemical source of monomers is available, the polymerase can survive on its own. When the chemical supply of monomers is too low, nucleotide production by the synthetase is essential and the two ribozymes can only survive when they are together. Here we consider a computational model to investigate conditions under which coexistence and cooperation of these two types of ribozymes is possible. The model considers six types of strands: the two functional sequences, the complementary strands to these sequences (which are required as templates), and non-functional mutants of the two sequences (which act as parasites). Strands are distributed on a two-dimensional lattice. Polymerases replicate strands on neighbouring sites and synthetases produce monomers that diffuse in the local neighbourhood. We show that coexistence of unlinked polymerases and synthetases is possible in this spatial model under conditions in which neither sequence could survive alone; hence, there is a selective force for increasing complexity. Coexistence is dependent on the relative lengths of the two functional strands, the strand diffusion rate, the monomer diffusion rate, and the rate of deleterious mutations. The sensitivity of this two-ribozyme system suggests that evolution of a system of many types of ribozymes would be difficult in a purely spatial model with unlinked genes. We therefore speculate that linkage of genes onto mini-chromosomes and encapsulation of strands in protocells would have been important fairly early in the history of life as a means of enabling more complex systems to evolve.

Trans-acting polymerases are cooperative, because they copy neighbouring strands, and do not copy themselves directly. Inaccurate replication creates parasitic strands that act as templates but not ribozymes. It is known that in spatially distributed models with slow strand diffusion, clusters of cooperating polymerases arise that can survive in the presence of parasites provided that the error rate is less than a maximum limit (the error threshold). In the RNA World, we envisage multiple types of ribozymes working together. We would like to understand how a multi-ribozyme system could evolve from a system with a single type of polymerase ribozyme. As a first step in increasing complexity, we consider a two-ribozyme system in which there is one polymerase and one nucleotide synthetase that produces monomers for use by the polymerase. We are particularly interested to find conditions in which the chemical supply of monomers is too low for the polymerase to survive alone, but the additional monomers created by the synthetase allow the two-ribozyme system to survive where the single-ribozyme system could not. There is then a selective force for increasing the complexity of the system. Here we show that spatial clustering is sufficient to allow cooperation and survival of systems of unlinked ribozymes with different functions. Clusters form in which synthetases form fringes around the polymerases. Survival of the two-ribozyme system depends on several factors. The strand diffusion rate must be slow enough for cooperative clusters to emerge. The replication rate of the polymerase must be comparable to that of the synthetase. The diffusion rate of the monomers must be neither too slow nor too fast. The model considers the most difficult case for cooperation–unlinked genes with no compartments. The sensitivity of the two-ribozyme system that we study here suggests that evolution of a spatial system with multiple unlinked ribozymes would become increasingly more difficult as the number of components increased, and suggests that linkage and protocells would need to evolve relatively early in the history of life.

Parasites Sustain and Enhance RNA-Like Replicators through Spatial Self-Organisation

In a prebiotic RNA world, parasitic behaviour may be favoured because template dependent replication happens in trans, thus being altruistic. Spatially extended systems are known to reduce harmful effects of parasites. Here we present a spatial system to show that evolution of replication is (indirectly) enhanced by strong parasites, and we characterise the phase transition that leads to this mode of evolution. Building on the insights of this analysis, we identify two scenarios, namely periodic disruptions and longer replication time-span, in which speciation occurs and an evolved parasite-like lineage enables the evolutionary increase of replication rates in replicators. Finally, we show that parasites co-evolving with replicators are selected to become weaker, i.e. worse templates for replication when the duration of replication is increased. We conclude that parasites may not be considered a problem for evolution in a prebiotic system, but a degree of freedom that can be exploited by evolution to enhance the evolvability of replicators, by means of emergent levels of selection.

The RNA world is a stage of evolution that preceded cellular life. In this world, RNA molecules would both replicate other RNAs and behave as templates for replication. A known evolutionary problem of this world is that selection should favour parasitic templates that do not replicate others, because they would be replicated the most. A possible solution to this problem comes from spatial self-organisation: local accumulation of parasites lead to their own local extinction, which leaves empty space for replicators to invade. We show that the spatial organisation generated by interacting replicators and parasites sets the (spatial) conditions that enhance replicase activity when parasites are stronger. Moreover, we find that the co-evolution of replicators and parasites is severely constrained by the type of spatial patterns they form, and we explore this feedback between evolution and self-organisation. We conclude that spatial self-organisation may have played a prominent role in prebiotic evolution.

Virus world as an evolutionary network of viruses and capsidless selfish elements

Viruses were defined as one of the two principal types of organisms in the biosphere, namely, as capsid-encoding organisms in contrast to ribosome-encoding organisms, i.e., all cellular life forms. Structurally similar, apparently homologous capsids are present in a huge variety of icosahedral viruses that infect bacteria, archaea, and eukaryotes. These findings prompted the concept of the capsid as the virus "self" that defines the identity of deep, ancient viral lineages. However, several other widespread viral "hallmark genes" encode key components of the viral replication apparatus (such as polymerases and helicases) and combine with different capsid proteins, given the inherently modular character of viral evolution. Furthermore, diverse, widespread, capsidless selfish genetic elements, such as plasmids and various types of transposons, share hallmark genes with viruses. Viruses appear to have evolved from capsidless selfish elements, and vice versa, on multiple occasions during evolution. At the earliest, precellular stage of life's evolution, capsidless genetic parasites most likely emerged first and subsequently gave rise to different classes of viruses. In this review, we develop the concept of a greater virus world which forms an evolutionary network that is held together by shared conserved genes and includes both bona fide capsid-encoding viruses and different classes of capsidless replicons. Theoretical studies indicate that selfish replicons (genetic parasites) inevitably emerge in any sufficiently complex evolving ensemble of replicators. Therefore, the key signature of the greater virus world is not the presence of a capsid but rather genetic, informational parasitism itself, i.e., various degrees of reliance on the information processing systems of the host.

The persistent contributions of RNA to eukaryotic gen(om)e architecture and cellular function

Currently, the best scenario for earliest forms of life is based on RNA molecules as they have the proven ability to catalyze enzymatic reactions and harbor genetic information. Evolutionary principles valid today become apparent in such models already. Furthermore, many features of eukaryotic genome architecture might have their origins in an RNA or RNA/protein (RNP) world, including the onset of a further transition, when DNA replaced RNA as the genetic bookkeeper of the cell. Chromosome maintenance, splicing, and regulatory function via RNA may be deeply rooted in the RNA/RNP worlds. Mostly in eukaryotes, conversion from RNA to DNA is still ongoing, which greatly impacts the plasticity of extant genomes. Raw material for novel genes encoding protein or RNA, or parts of genes including regulatory elements that selection can act on, continues to enter the evolutionary lottery.

Evolution of functional diversification within quasispecies

According to quasispecies theory, high mutation rates limit the amount of information genomes can store (Eigen’s Paradox), whereas genomes with higher degrees of neutrality may be selected even at the expenses of higher replication rates (the “survival of the flattest” effect). Introducing a complex genotype to phenotype map, such as RNA folding, epitomizes such effect because of the existence of neutral networks and their exploitation by evolution, affecting both population structure and genome composition. We reexamine these classical results in the light of an RNA-based system that can evolve its own ecology. Contrary to expectations, we find that quasispecies evolving at high mutation rates are steep and characterized by one master sequence. Importantly, the analysis of the system and the characterization of the evolved quasispecies reveal the emergence of functionalities as phenotypes of nonreplicating genotypes, whose presence is crucial for the overall viability and stability of the system. In other words, the master sequence codes for the information of the entire ecosystem, whereas the decoding happens, stochastically, through mutations. We show that this solution quickly outcompetes strategies based on genomes with a high degree of neutrality. In conclusion, individually coded but ecosystem-based diversity evolves and persists indefinitely close to the Information Threshold.

The origins of cellular life

All life on earth can be naturally classified into cellular life forms and virus-like selfish elements, the latter being fully dependent on the former for their reproduction. Cells are reproducers that not only replicate their genome but also reproduce the cellular organization that depends on semipermeable, energy-transforming membranes and cannot be recovered from the genome alone, under the famous dictum of Rudolf Virchow, Omnis cellula e cellula. In contrast, simple selfish elements are replicators that can complete their life cycles within the host cell starting from genomic RNA or DNA alone. The origin of the cellular organization is the central and perhaps the hardest problem of evolutionary biology. I argue that the origin of cells can be understood only in conjunction with the origin and evolution of selfish genetic elements. A scenario of precellular evolution is presented that involves cohesion of the genomes of the emerging cellular life forms from primordial pools of small genetic elements that eventually segregated into hosts and parasites. I further present a model of the coevolution of primordial membranes and membrane proteins, discuss protocellular and non-cellular models of early evolution, and examine the habitats on the primordial earth that could have been conducive to precellular evolution and the origin of cells.

A virocentric perspective on the evolution of life

Viruses and/or virus-like selfish elements are associated with all cellular life forms and are the most abundant biological entities on Earth, with the number of virus particles in many environments exceeding the number of cells by one to two orders of magnitude. The genetic diversity of viruses is commensurately enormous and might substantially exceed the diversity of cellular organisms. Unlike cellular organisms with their uniform replication-expression scheme, viruses possess either RNA or DNA genomes and exploit all conceivable replication-expression strategies. Although viruses extensively exchange genes with their hosts, there exists a set of viral hallmark genes that are shared by extremely diverse groups of viruses to the exclusion of cellular life forms. Coevolution of viruses and host defense systems is a key aspect in the evolution of both viruses and cells, and viral genes are often recruited for cellular functions. Together with the fundamental inevitability of the emergence of genomic parasites in any evolving replicator system, these multiple lines of evidence reveal the central role of viruses in the entire evolution of life.

Evolutionary dynamics of RNA-like replicator systems: A bioinformatic approach to the origin of life

We review computational studies on prebiotic evolution, focusing on informatic processes in RNA-like replicator systems. In particular, we consider the following processes: the maintenance of information by replicators with and without interactions, the acquisition of information by replicators having a complex genotype-phenotype map, the generation of information by replicators having a complex genotype-phenotype-interaction map, and the storage of information by replicators serving as dedicated templates. Focusing on these informatic aspects, we review studies on quasi-species, error threshold, RNA-folding genotype-phenotype map, hypercycle, multilevel selection (including spatial self-organization, classical group selection, and compartmentalization), and the origin of DNA-like replicators. In conclusion, we pose a future question for theoretical studies on the origin of life.

Less can be more: RNA-adapters may enhance coding capacity of replicators

It is still not clear how prebiotic replicators evolved towards the complexity found in present day organisms. Within the most realistic scenario for prebiotic evolution, known as the RNA world hypothesis, such complexity has arisen from replicators consisting solely of RNA. Within contemporary life, remarkably many RNAs are involved in modifying other RNAs. In hindsight, such RNA-RNA modification might have helped in alleviating the limits of complexity posed by the information threshold for RNA-only replicators. Here we study the possible role of such self-modification in early evolution, by modeling the evolution of protocells as evolving replicators, which have the opportunity to incorporate these mechanisms as a molecular tool. Evolution is studied towards a set of 25 arbitrary 'functional' structures, while avoiding all other (misfolded) structures, which are considered to be toxic and increase the death-rate of a protocell. The modeled protocells contain a genotype of different RNA-sequences while their phenotype is the ensemble of secondary structures they can potentially produce from these RNA-sequences. One of the secondary structures explicitly codes for a simple sequence-modification tool. This 'RNA-adapter' can block certain positions on other RNA-sequences through antisense base-pairing. The altered sequence can produce an alternative secondary structure, which may or may not be functional. We show that the modifying potential of interacting RNA-sequences enables these protocells to evolve high fitness under high mutation rates. Moreover, our model shows that because of toxicity of misfolded molecules, redundant coding impedes the evolution of self-modification machinery, in effect restraining the evolvability of coding structures. Hence, high mutation rates can actually promote the evolution of complex coding structures by reducing redundant coding. Protocells can successfully use RNA-adapters to modify their genotype-phenotype mapping in order to enhance the coding capacity of their genome and fit more information on smaller sized genomes.

Patch depletion, niche structuring and the evolution of co-operative foraging

BACKGROUND

Many animals live in groups. One proposed reason is that grouping allows cooperative food finding. Group foraging models suggest that grouping could increase food finding rates, but that such group processes could be evolutionarily unstable. These models assume discrete food patches which are fully detectable. However, often animals may only be able to perceive local parts of larger-scale environmental patterns. We therefore use a spatial individual-based model where food patches are aggregates of food items beyond the scale of individual perception. We then study the evolution of foraging and grouping behavior in environments with different resource distributions.

RESULTS

Our results show that grouping can evolve to increase food intake rates. Two kinds of grouping evolve: traveling pairs and opportunistic grouping, where individuals only aggregate when feeding. Grouping evolves because it allows individuals to better sense and deplete patches. Such enhanced patch depletion is particularly apparent on fragmented and partially depleted patches, which are especially difficult for solitary foragers to deplete. Solitary foragers often leave a patch prematurely because a whole patch cannot be observed directly. In groups, individuals that are still eating allow other individuals that inadvertently leave the patch, to return and continue feeding. For this information sharing a grouping tendency is sufficient and observing whether a neighbor is eating is not necessary. Grouping therefore leads to a release from individual sensing constraints and a shift in niche specialization, allowing individuals to better exploit partially depleted patches.

CONCLUSIONS

The evolved group foraging can be seen as cooperative in the sense that it leads to a mutually-beneficial synergy: together individuals can achieve more than on their own. This cooperation exists as a group-level process generated by the interaction between grouping and the environment. Thus we reveal how such a synergy can originate in evolution as a side-effect of grouping via multi-level selection. Here there is no cooperative dilemma as individuals cannot avoid producing information for their neighbors. This scenario may be a useful starting point for studying the evolution of further social and cooperative complexity.

Defense islands in bacterial and archaeal genomes and prediction of novel defense systems

The arms race between cellular life forms and viruses is a major driving force of evolution. A substantial fraction of bacterial and archaeal genomes is dedicated to antivirus defense. We analyzed the distribution of defense genes and typical mobilome components (such as viral and transposon genes) in bacterial and archaeal genomes and demonstrated statistically significant clustering of antivirus defense systems and mobile genes and elements in genomic islands. The defense islands are enriched in putative operons and contain numerous overrepresented gene families. A detailed sequence analysis of the proteins encoded by genes in these families shows that many of them are diverged variants of known defense system components, whereas others show features, such as characteristic operonic organization, that are suggestive of novel defense systems. Thus, genomic islands provide abundant material for the experimental study of bacterial and archaeal antivirus defense. Except for the CRISPR-Cas systems, different classes of defense systems, in particular toxin-antitoxin and restriction-modification systems, show nonrandom clustering in defense islands. It remains unclear to what extent these associations reflect functional cooperation between different defense systems and to what extent the islands are genomic "sinks" that accumulate diverse nonessential genes, particularly those acquired via horizontal gene transfer. The characteristics of defense islands resemble those of mobilome islands. Defense and mobilome genes are nonrandomly associated in islands, suggesting nonadaptive evolution of the islands via a preferential attachment-like mechanism underpinned by the addictive properties of defense systems such as toxins-antitoxins and an important role of horizontal mobility in the evolution of these islands.

On the origin of DNA genomes: evolution of the division of labor between template and catalyst in model replicator systems

The division of labor between template and catalyst is a fundamental property of all living systems: DNA stores genetic information whereas proteins function as catalysts. The RNA world hypothesis, however, posits that, at the earlier stages of evolution, RNA acted as both template and catalyst. Why would such division of labor evolve in the RNA world? We investigated the evolution of DNA-like molecules, i.e. molecules that can function only as template, in minimal computational models of RNA replicator systems. In the models, RNA can function as both template-directed polymerase and template, whereas DNA can function only as template. Two classes of models were explored. In the surface models, replicators are attached to surfaces with finite diffusion. In the compartment models, replicators are compartmentalized by vesicle-like boundaries. Both models displayed the evolution of DNA and the ensuing division of labor between templates and catalysts. In the surface model, DNA provides the advantage of greater resistance against parasitic templates. However, this advantage is at least partially offset by the disadvantage of slower multiplication due to the increased complexity of the replication cycle. In the compartment model, DNA can significantly delay the intra-compartment evolution of RNA towards catalytic deterioration. These results are explained in terms of the trade-off between template and catalyst that is inherent in RNA-only replication cycles: DNA releases RNA from this trade-off by making it unnecessary for RNA to serve as template and so rendering the system more resistant against evolving parasitism. Our analysis of these simple models suggests that the lack of catalytic activity in DNA by itself can generate a sufficient selective advantage for RNA replicator systems to produce DNA. Given the widespread notion that DNA evolved owing to its superior chemical properties as a template, this study offers a novel insight into the evolutionary origin of DNA.

At the core of all biological systems lies the division of labor between the storage of genetic information and its phenotypic implementation, in other words, the functional differentiation between templates (DNA) and catalysts (proteins). This fundamental property of life is believed to have been absent at the earliest stages of evolution. The RNA world hypothesis, the most realistic current scenario for the origin of life, posits that, in primordial replicating systems, RNA functioned both as template and as catalyst. How would such division of labor emerge through Darwinian evolution? We investigated the evolution of DNA-like molecules in minimal computational models of RNA replicator systems. Two models were considered: one where molecules are adsorbed on surfaces and another one where molecules are compartmentalized by dividing cellular boundaries. Both models exhibit the evolution of DNA and the ensuing division of labor, revealing the simple governing principle of these processes: DNA releases RNA from the trade-off between template and catalyst that is inevitable in the RNA world and thereby enhances the system's resistance against parasitic templates. Hence, this study offers a novel insight into the evolutionary origin of the division of labor between templates and catalysts in the RNA world.

Eco-evolutionary dynamics, coding structure and the information threshold

Background

The amount of information that can be maintained in an evolutionary system of replicators is limited by genome length, the number of errors during replication (mutation rate) and various external factors that influence the selection pressure. To date, this phenomenon, known as the information threshold, has been studied (both genotypically and phenotypically) in a constant environment and with respect to maintenance (as opposed to accumulation) of information. Here we take a broader perspective on this problem by studying the accumulation of information in an ecosystem, given an evolvable coding structure. Moreover, our setup allows for individual based as well as ecosystem based solutions. That is, all functions can be performed by individual replicators, or complementing functions can be performed by different replicators. In this setup, where both the ecosystem and the individual genomes can evolve their structure, we study how populations cope with high mutation rates and accordingly how the information threshold might be alleviated.

Results

We observe that the first response to increased mutation rates is a change in coding structure. At moderate mutation rates evolution leads to longer genomes with a higher diversity than at high mutation rates. Thus, counter-intuitively, at higher mutation rates diversity is reduced and the efficacy of the evolutionary process is decreased. Therefore, moderate mutation rates allow for more degrees of freedom in exploring genotype space during the evolutionary trajectory, facilitating the emergence of solutions. When an individual based solution cannot be attained due to high mutation rates, spatial structuring of the ecosystem can accommodate the evolution of ecosystem based solutions.

Conclusions

We conclude that the evolutionary freedom (eg. the number of genotypes that can be reached by evolution) is increasingly restricted by higher mutation rates. In the case of such severe mutation rates that an individual based solution cannot be evolved, the ecosystem can take over and still process the required information forming ecosystem based solutions. We provide a proof of principle for species fulfilling the different roles in an ecosystem when single replicators can no longer cope with all functions simultaneously. This could be a first step in crossing the information threshold.

Dynamics of a laterally evolving community of ribozyme-like agents as studied with a rule-based computing system

The very early forms of life probably comprised ribozyme-like agents that were able to catalyze reactions and serve as templates for their own replication. The early evolution has also been suggested to occur mainly horizontally between proto-cells or inorganic compartments rather than vertically from parent cell to their dividing siblings. In order to study the evolutionary dynamics of such a community a rule-based computing system entitled as PrimordialEvo was developed. The system simulates a three dimensional matrix of compartments in which replicators, resource collectors and various other actors thrive. Horizontal movement between compartments may be due to genetically induced vesicle formation or random drift. Analysis of the simulation experiments suggests that active sharing of innovations between compartments is important for the overall reproductive success of life. The capability of natural selection to favor genes in the system was also tested, and, for example, the frequency of anti-parasites was observed to increase when parasites were allowed to emerge.

Genotype-phenotype mapping and the end of the 'genes as blueprint' metaphor

In a now classic paper published in 1991, Alberch introduced the concept of genotype-phenotype (G-->P) mapping to provide a framework for a more sophisticated discussion of the integration between genetics and developmental biology that was then available. The advent of evo-devo first and of the genomic era later would seem to have superseded talk of transitions in phenotypic space and the like, central to Alberch's approach. On the contrary, this paper shows that recent empirical and theoretical advances have only sharpened the need for a different conceptual treatment of how phenotypes are produced. Old-fashioned metaphors like genetic blueprint and genetic programme are not only woefully inadequate but positively misleading about the nature of G-->P, and are being replaced by an algorithmic approach emerging from the study of a variety of actual G-->P maps. These include RNA folding, protein function and the study of evolvable software. Some generalities are emerging from these disparate fields of analysis, and I suggest that the concept of 'developmental encoding' (as opposed to the classical one of genetic encoding) provides a promising computational-theoretical underpinning to coherently integrate ideas on evolvability, modularity and robustness and foster a fruitful framing of the G-->P mapping problem.

Multilevel selection in models of prebiotic evolution II: a direct comparison of compartmentalization and spatial self-organization

Multilevel selection has been indicated as an essential factor for the evolution of complexity in interacting RNA-like replicator systems. There are two types of multilevel selection mechanisms: implicit and explicit. For implicit multilevel selection, spatial self-organization of replicator populations has been suggested, which leads to higher level selection among emergent mesoscopic spatial patterns (traveling waves). For explicit multilevel selection, compartmentalization of replicators by vesicles has been suggested, which leads to higher level evolutionary dynamics among explicitly imposed mesoscopic entities (protocells). Historically, these mechanisms have been given separate consideration for the interests on its own. Here, we make a direct comparison between spatial self-organization and compartmentalization in simulated RNA-like replicator systems. Firstly, we show that both mechanisms achieve the macroscopic stability of a replicator system through the evolutionary dynamics on mesoscopic entities that counteract that of microscopic entities. Secondly, we show that a striking difference exists between the two mechanisms regarding their possible influence on the long-term evolutionary dynamics, which happens under an emergent trade-off situation arising from the multilevel selection. The difference is explained in terms of the difference in the stability between self-organized mesoscopic entities and externally imposed mesoscopic entities. Thirdly, we show that a sharp transition happens in the long-term evolutionary dynamics of the compartmentalized system as a function of replicator mutation rate. Fourthly, the results imply that spatial self-organization can allow the evolution of stable folding in parasitic replicators without any specific functionality in the folding itself. Finally, the results are discussed in relation to the experimental synthesis of chemical Darwinian systems and to the multilevel selection theory of evolutionary biology in general. To conclude, novel evolutionary directions can emerge through interactions between the evolutionary dynamics on multiple levels of organization. Different multilevel selection mechanisms can produce a difference in the long-term evolutionary trend of identical microscopic entities.

The origin of life has ever been attracting scientific inquiries. The RNA world hypothesis suggests that, before the evolution of DNA and protein, primordial life was based on RNA-like molecules both for information storage and chemical catalysis. In the simplest form, an RNA world consists of RNA molecules that can catalyze the replication of their own copies. Thus, an interesting question is whether a system of RNA-like replicators can increase its complexity through Darwinian evolution and approach the modern form of life. It is, however, known that simple natural selection acting on individual replicators is insufficient to account for the evolution of complexity due to the evolution of parasite-like templates. Two solutions have been suggested: compartmentalization of replicators by membranes (i.e., protocells) and spatial self-organization of a replicator population. Here, we make a direct comparison of the two suggestions by computer simulations. Our results show that the two suggestions can lead to unanticipated and contrasting consequences in the long-term evolution of replicating molecules. The results also imply a novel advantage in the spatial self-organization for the evolution of complexity in RNA-like replicator systems.

Evolution of resource cycling in ecosystems and individuals

BACKGROUND

Resource cycling is a defining process in the maintenance of the biosphere. Microbial communities, ranging from simple to highly diverse, play a crucial role in this process. Yet the evolutionary adaptation and speciation of micro-organisms have rarely been studied in the context of resource cycling. In this study, our basic questions are how does a community evolve its resource usage and how are resource cycles partitioned?

RESULTS

We design a computational model in which a population of individuals evolves to take up nutrients and excrete waste. The waste of one individual is another's resource. Given a fixed amount of resources, this leads to resource cycles. We find that the shortest cycle dominates the ecological dynamics, and over evolutionary time its length is minimized. Initially a single lineage processes a long cycle of resources, later crossfeeding lineages arise. The evolutionary dynamics that follow are determined by the strength of indirect selection for resource cycling. We study indirect selection by changing the spatial setting and the strength of direct selection. If individuals are fixed at lattice sites or direct selection is low, indirect selection result in lineages that structure their local environment, leading to 'smart' individuals and stable patterns of resource dynamics. The individuals are good at cycling resources themselves and do this with a short cycle. On the other hand, if individuals randomly change position each time step, or direct selection is high, individuals are more prone to crossfeeding: an ecosystem based solution with turbulent resource dynamics, and individuals that are less capable of cycling resources themselves.

CONCLUSION

In a baseline model of ecosystem evolution we demonstrate different eco-evolutionary trajectories of resource cycling. By varying the strength of indirect selection through the spatial setting and direct selection, the integration of information by the evolutionary process leads to qualitatively different results from individual smartness to cooperative community structures.

The dawn of the RNA World: toward functional complexity through ligation of random RNA oligomers

A main unsolved problem in the RNA World scenario for the origin of life is how a template-dependent RNA polymerase ribozyme emerged from short RNA oligomers obtained by random polymerization on mineral surfaces. A number of computational studies have shown that the structural repertoire yielded by that process is dominated by topologically simple structures, notably hairpin-like ones. A fraction of these could display RNA ligase activity and catalyze the assembly of larger, eventually functional RNA molecules retaining their previous modular structure: molecular complexity increases but template replication is absent. This allows us to build up a stepwise model of ligation-based, modular evolution that could pave the way to the emergence of a ribozyme with RNA replicase activity, step at which information-driven Darwinian evolution would be triggered.

The pig as a mixing vessel for influenza viruses: Human and veterinary implications

Influenza A viruses are highly infectious respiratory pathogens that can infect many species. Birds are the reservoir for all known influenza A subtypes; and novel influenza viruses can emerge from birds and infect mammalian species including humans. Because swine are susceptible to infection with both avian and human influenza viruses, novel reassortant influenza viruses can be generated in this mammalian species by reassortment of influenza viral segments leading to the "mixing vessel" theory. There is no direct evidence that the reassortment events culminating in the 1918, 1957 or 1968 pandemic influenza viruses originated from pigs. Genetic reassortment among avian, human and/or swine influenza virus gene segments has occurred in pigs and some novel reassortant swine viruses have been transmitted to humans. Notably, novel reassortant H2N3 influenza viruses isolated from the US pigs, most likely infected with avian influenza viruses through surface water collected in ponds for cleaning barns and watering animals, had a similar genetic make-up to early isolates (1957) of the H2N2 human pandemic. These novel H2N3 swine viruses were able to cause disease in swine and mice and were infectious and highly transmissible in swine and ferrets without prior adaptation. The preceding example shows that pigs could transmit novel viruses from an avian reservoir to other mammalian species. Importantly, H2 viruses pose a substantial risk to humans because they have been absent from mammalian species since 1968 and people born after 1968 have little preexisting immunity to the H2 subtype. It is difficult to predict which virus will cause the next human pandemic and when that pandemic might begin. Importantly, the establishment and spread of a reassorted mammalian-adapted virus from pigs to humans could happen anywhere in the world. Therefore, both human and veterinary research needs to give more attention to potential cross-species transmission capacity of influenza A viruses.

Prebiotic replicase evolution in a surface-bound metabolic system: parasites as a source of adaptive evolution

Background

The remarkable potential of recent forms of life for reliably passing on genetic information through many generations now depends on the coordinated action of thousands of specialized biochemical "machines" (enzymes) that were obviously absent in prebiotic times. Thus the question how a complicated system like the living cell could have assembled on Earth seems puzzling. In seeking for a scientific explanation one has to search for step-by-step evolutionary changes from prebiotic chemistry to the emergence of the first proto-cell.

Results

We try to sketch a plausible scenario for the first steps of prebiotic evolution by exploring the ecological feasibility of a mineral surface-bound replicator system that facilitates a primitive metabolism. Metabolism is a hypothetical network of simple chemical reactions producing monomers for the template-copying of RNA-like replicators, which in turn catalyse metabolic reactions. Using stochastic cellular automata (SCA) simulations we show that the surface-bound metabolic replicator system is viable despite internal competition among the genes and that it also maintains a set of mild "parasitic" sequences which occasionally evolve functions such as that of a replicase.

Conclusion

Replicase activity is shown to increase even at the expense of slowing down the replication of the evolving ribozyme itself, due to indirect mutualistic benefits in a diffuse form of group selection among neighbouring replicators. We suggest possible paths for further evolutionary changes in the metabolic replicator system leading to increased metabolic efficiency, improved replicase functionality, and membrane production.

The evolution of strand preference in simulated RNA replicators with strand displacement: implications for the origin of transcription

Background

The simplest conceivable example of evolving systems is RNA molecules that can replicate themselves. Since replication produces a new RNA strand complementary to a template, all templates would eventually become double-stranded and, hence, become unavailable for replication. Thus the problem of how to separate the two strands is considered a major issue for the early evolution of self-replicating RNA. One biologically plausible way to copy a double-stranded RNA is to displace a preexisting strand by a newly synthesized strand. Such copying can in principle be initiated from either the (+) or (-) strand of a double-stranded RNA. Assuming that only one of them, say (+), can act as replicase when single-stranded, strand displacement produces a new replicase if the (-) strand is the template. If, however, the (+) strand is the template, it produces a new template (but no replicase). Modern transcription exhibits extreme strand preference wherein anti-sense strands are always the template. Likewise, replication by strand displacement seems optimal if it also exhibits extreme strand preference wherein (-) strands are always the template, favoring replicase production. Here we investigate whether such strand preference can evolve in a simple RNA replicator system with strand displacement.

Results

We first studied a simple mathematical model of the replicator dynamics. Our results indicated that if the system is well-mixed, there is no selective force acting upon strand preference per se. Next, we studied an individual-based simulation model to investigate the evolution of strand preference under finite diffusion. Interestingly, the results showed that selective forces "emerge" because of finite diffusion. Strikingly, the direction of the strand preference that evolves [i.e. (+) or (-) strand excess] is a complex non-monotonic function of the diffusion intensity. The mechanism underlying this behavior is elucidated. Furthermore, a speciation-like phenomenon is observed under certain conditions: two extreme replication strategies, namely replicase producers and template producers, emerge and coexist among competing replicators.

Conclusion

Finite diffusion enables the evolution of strand preference, the direction of which is a non-monotonic function of the diffusion intensity. By identifying the conditions under which strand preference evolves, this study provides an insight into how a rudimentary transcription-like pattern might have emerged in an RNA-based replicator system.

Reviewers

This article was reviewed by Eugene V Koonin, Rob Kinght and István Scheuring (nominated by David H Ardell). For the full reviews, please go to the Reviewers' comments section.